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Amazon has designed a floating warehouse that sits thousands of feet in the air, from which the internet retailer could dispatch swarms of delivery drones to metropolitan areas.

The company has patented futuristic plans for enormous “airborne fulfillment centres” that would be used as bases for aerial deliveries to homes.

Flying at up to 45,000 feet, the warehouses would be suspended by cables from zeppelin-style airships, and stocked with popular items. When a shopper makes an order, an onboard drone would dive down to earth and deliver it, before being sent back up to the station by a shuttle that could also restock and refuel the floating warehouse.

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(NaturalNews) A diagnosis of amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig’s disease, was once considered a death sentence, but advanced automation technology is offering new hope to sufferers of the rare condition.

Most ALS patients eventually face an extremely difficult choice: either die from the lack of ability to breathe once the disease progresses or undergo a tracheostomy and spend the rest of one’s life on a ventilator – unable to move or speak.

Less than 10 percent of ALS patients choose the second option, but one man who suffers from the disease is helping to develop a viable third option: an opportunity to lead a relatively independent and mobile existence with the help of automation technology that can respond to head and eye movements, or even brain waves.

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A man with deadly brain cancer that had spread to his spine saw his tumors shrink and, for a time, completely vanish after a novel treatment to help his immune system attack his disease — another first in this promising field.

The type of immunotherapy that 50-year-old Richard Grady received already has helped some people with blood cancers such as leukemia. But the way he was given it is new, and may allow its use not just for brain tumors but also other cancers that can spread, such as breast and lung.

Grady was the first person to get the treatment dripped through a tube into a space in the brain where spinal fluid is made, sending it down the path the cancer traveled to his spine.

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Constructing gene circuits that satisfy quantitative performance criteria has been a long‐standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three‐gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high‐throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor reprogramming and biosensor integration into larger networks, enabling in principle arbitrary logic with miRNA inputs using normal form circuits. The study reveals how model‐guided generation of genetic diversity followed by screening and model validation can be successfully applied to optimize performance of complex gene networks without extensive prior knowledge.

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